Damage Prediction Report Extension to Dutch Utility Information System

Key Parameters

Risks

▪ Difficulty in collecting data because of distributed and large numbers of data providers.

▪ Difficulty in predicting which cables/pipelines are likely to be broken by an excavation project.

Continuum–DEM modelling of the fluid–solid transition in weakly compacted systems of polydisperse particles of varying shapes

Keywords: granular materials, fluid-solid transition, uniform flowability, continuum methods, up-Scaling

Retief Lubbe*1,2, Prof.VanessaMagnanimo1 , Prof.StefanLuding1,Dr.HongyangCheng1 , Dr.PrashantGupta2

University of Twente, Netherlands1

Procter&GambleTechnicalCentre,UnitedKingdom2

Main take aways:

• Granular materials are solid-like and fluidlike

• Irregular flows are a challenge in industry

• Numerical solution for fluid-solid transition is necessary

Introduction

• Depending on how granularmaterials are handled, they can behave like fluid or solid

• The fluid-solidtransition poses a significantchallenge in industry

• Solution is to develop a tool to virtually prototype designs to reduce wasteful resources

Preliminary work

• Performed an extensive literaturereview on state of the art

• Developed and verified 3D GPU MPM solver

• Implementedconstitutivemodels: isotropic linear elasticity, Newtonian fluid, ��-I rheology (granular material)

Conclusion

Main theoretical concepts

• Develop a continuum-discrete solver to capture the fluid-solid transition of granular materials

• Study the influence of polydisperse and multi -component systems on the flowability

• Study the influence of the geometry (equipment) on the flowability

Methods

• Irregular flow of granular material is challenging in industry

• MPM is well suited for granular flow problems

• Continuum solution is needed to capture the transition at an industrial scale

Global trends in water footprints of crop production

#waterfootprint #agriculture #modelling #sustainability

Oleksandr Mialyk, Joep F. Schyns, Martijn J. Booij, Markus Berger Multidisciplinary Water Management | University of Twente, Netherlands

Huston, we have a problem!

• Crop production is responsible for most of humanity’s water consumption

• Water is getting scarcer in many places

• Increase in crop production is needed to sustain the future global population

• So we need more food but with less water

What are we trying to do?

• Estimate water footprints of global crop production over 1990-2019

• Run process-based global crop model at high spatial resolution covering 160 crops

• Analise the key drivers for trends in water footprints to identify the main challenges

How does it work?

• Planet is divided into a grid of 10x10 km

• In each grid cell, a numerical model simulates the growth of local crops

• Water footprint (m3 t-1) is calculated by dividing crop water use by yields

What do we find?

-25% average water footprint

+80% total crop production

+36% total water consumption

What does it mean?

50% consumed by maize, wheat, rice, and soybean

• The reduction in water footprints of crops is outpaced by the increase in production

• As a result, the total water consumption is increasing and just four crops are responsible for half of it

• In future, the competition for water resources is likely to increase, leading to more scarcity and subsequent issues (biodiversity loss, social unrest, food market instability etc.)

What can be done?

• Further reduction of water footprints of crops, especially in the underdeveloped regions

• Optimise global food systems and diets to satisfy humanity’s needs without further increase in crop production

Email: o.mialyk@utwente.nl

To replace or not to replace: a model for future functional performance of bridges

Asset Management; Bridges; Functional Performance

Sander Mooren*, Andreas Hartmann, Sahand Asgarpour; CME | University of Twente, Netherlands

Introduction

▪ Asset managers at road agency are, among other tasks, responsible for managing bridges. A focus exists on technical and economic end-of-life, although in practice bridges often get replaced for functional shortcoming; the functional performance no longer meets the functional requirements.

▪ Asset managers aim to optimise value by balancing life cycle costs, risks and performance. Nevertheless, it is a challenge to formulate bridges’ life cycle performance. For this thesis, a model has been developed to aid asset managers by providing insight into the future functional performance level of bridges.

▪ Research question: How does functional performance of bridges and viaducts as part of a network develop over time (1) and how can these insights contribute to infrastructure asset management decision making (2)?

Research design

▪ A model has been developed to forecast bridges’ functional performance level. The develop model has been built as an extension to a base model. The base model contains road segments’ traffic intensity and capacity from 2019 to 2050 under 4 future scenarios. The scope of the model is national roads in the Randstad area in the Netherlands.

▪ Expert interviews, scientific literature, internal documents from Dutch road agency Rijkswaterstaat, and legal documentation have been used in the development of the model.

▪ First, indicators for bridges’ functional performance have been selected. Subsequently, a theoretical foundation for these indicators has been built, before software implementation took place. After implementing the model and running the simulation for 4 scenarios, the output has been reshaped to present it in various different visualisations.

Results

▪ The selected indicators are: Intensity/Capacity ratio, Automatic Incident Detection (AID), Lighting, Noise.

▪ 1183 bridges have been linked to the base model.

▪ The simulation’s output gives a 4-dimensional data cube (bridges, indicators, time, scenario)

▪ By performing different operations on the data cube, asset managers obtain various visualisations. This gives asset manager more insight into the functional performance of bridges.

Discussions

▪ The base model is not flawless in its traffic assignment. As a result, the model may prematurely label a bridge as having reached its functional end-of-life.

▪ The traffic intensity of the other side of the viaduct is in many cases unknown. Thus, a bridge could reach its functional end-of-life which the model does not identify.

Conclusion

▪ The developed model allows asset managers to account for the future functional performance level of bridges. As a result, interventions can be scheduled more efficaciously.

Software development to estimate the Pavement-Vehicle Interaction (PVI) effects on vehicle fuel consumption

Keywords: Rolling resistance, Fuel consumption, CO2 emissions

Ida Noemi Uva*, João Santos, Seirgei Miller, Andre Doree, Faculty of Engineering Technology, Department of Construction and Management Engineering (CME) | University of Twente, Netherlands

Introduction

Nowadays, worldwide attention is focused on the global warming that arises from significant greenhouse (GHG) emissions CO2 is a major contributor to GHG emissions, and the transportation sector is responsible for a great share of the total emissions Further, a considerable percentage of CO2 emissions is related to vehicle fuel consumption and rolling resistance represents its primary source

Research objective

The main research objective concerns the development of a software that deploys data-driven models to predict rolling resistance and its effects on additional vehicle fuel consumption.

What is rolling resistance?

The rolling resistance is one of the resistive forces acting on the vehicle In simple terms, it is a force opposing the movement of a body (i e , tire) on a pavement surface